dart_openai 1.1.2 dart_openai: ^1.1.2 copied to clipboard
Dart SDK for openAI Apis (GPT-3 & DALL-E), integrate easily the power of OpenAI's state-of-the-art AI models into their Dart applications.
Dart Client For OpenAI (GPT-3 & DALL-E..) #
An open-source Client package that allows developers to easily integrate the power of OpenAI's state-of-the-art AI models into their Dart/Flutter applications.
This library provides simple and intuitive methods for making requests to OpenAI's various APIs, including the GPT-3 language model, DALL-E image generation, and more.
The package is designed to be lightweight and easy to use, so you can focus on building your application, rather than worrying about the complexities and errors caused by dealing with HTTP requests.
Unofficial
OpenAI does not have any official Dart library.
Note:
Please note that this client SDK connects directly to OpenAI APIs using HTTP requests.
Key Features #
-
Easy to use methods that reflect exactly the OpenAI documentation, with additional functionalities that make it better to use with Dart Programming Language.
-
Authorize just once, use it anywhere and at any time in your application
-
Developer-friendly.
-
Stream
functionality for completions API.
Code Progress (100 %) #
- ✅ Authentication
- ✅ Models
- ✅ Completions
- ✅ With
Stream
responses
- ✅ With
- ✅ Edits
- ✅ Images
- ✅ Embeddings
- ✅ Files
- ✅ Fine-tunes
- ❌ With events
Stream
responses
- ❌ With events
- ✅ Moderation
- ❌ ChatGPT ( as soon as possible when it's released )
Testing Progress (100 %) #
- ✅ Authentication
- ✅ Models
- ✅ Completions
- ✅ Edits
- ✅ Images
- ✅ Embeddings
- ✅ Files
- ✅ Fine-tunes
- ✅ Moderation
Full Documentation: #
For the full documentation about all members this library offers, check here.
Usage #
Authentication #
API key
The OpenAI API uses API keys for authentication. you can get your account APU key by visiting API keys of your account.
We highly recommend loading your secret key at runtime from a .env
file, you can use the dotenv package for Dart applications or flutter_dotenv](https://pub.dev/packages/flutter_dotenv) for Flutter's.
void main() {
DotEnv env = DotEnv()..load([".env"]); // Loads our .env file.
OpenAI.apiKey = env['OPEN_AI_API_KEY']; // Initialize the package with that API key
// ..
}
if no apiKey
is set, and you tried to access [OpenAI.instance], a MissingApiKeyException
will be thrown even before making the actual request.
if the apiKey
is set, but it is invalid when making requests, a RequestFailedException
will be thrown in your app, check the error handling section for more info.
Setting an organization
if you belong to a specific organization, you can pass the its id to OpenAI.organization
like this:
OpenAI.organization = "ORGANIZATION ID";
If you don't belong actually to any organization, you can just ignore this section, or set it to null
.
Models #
List Models
Lists the currently available models, and provides basic information about each one such as the owner and availability.
List<OpenAIModelModel> models = await OpenAI.instance.model.list();
OpenAIModelModel firstModel = models.first;
print(firstModel.id); // ...
Retrieve model.
Retrieves a single model by its id and get additional pieces of information about it.
final model = await OpenAI.instance.model.retrieve("text-davinci-003");
print(model.id)
If the model id does not exists, a RequestFailedException
will be thrown, check Error Handling section
Completions #
Create completion
Creates a Completion based on the provided properties :
OpenAICompletionModel completion = await OpenAI.instance.completion.create(
model: "text-davinci-003",
prompt: "Dart is a progr",
maxTokens: 20,
temperature: 0.5,
n: 1,
stop: ["\n"],
echo: true,
);
Edits #
Create edit
OpenAIEditModel edit = await OpenAI.instance.edit.create(
model: "text-davinci-edit-001",
input: " Hi!, I am a bot!!!!,",
instruction: "remove all ! the input ",
);
Images #
Create image
OpenAIImageModel image = await OpenAI.instance.image.create(
prompt: "A dog",
n: 1,
);
Create image edit
final result = await OpenAI.instance.image.edit(
image: File(/* image file path*/),
mask: File(/* mask file path*/),
prompt: "change color to green",
n: 1,
);
Create image variation
OpenAIImageVariationModel variation = await OpenAI.instance.image.variation(
image: File(/*YOUR IMAGE FILE PATH*/),
);
Embeddings #
Create embeddings
OpenAIEmbeddingsModel embeddings = await OpenAI.instance.embedding.create(
model: "text-embedding-ada-002",
input: "This is a text input just to test",
);;
Files #
List files
List<OpenAIFileModel> files = await OpenAI.instance.file.list();
Upload file
OpenAIFileModel uploadedFile = await OpenAI.instance.file.upload(
file: File("FILE PATH HERE"),
purpose: "fine-tuning",
);
Delete file
bool isFileDeleted = await OpenAI.instance.file.delete("FILE ID");
Retrieve file
OpenAIFileModel file = await OpenAI.instance.file.retrieve("FILE ID");
Retrieve file content
dynamic fileContent = await OpenAI.instance.file.retrieveContent("FILE ID");
Fine Tunes #
Create fine-tune
OpenAIFineTuneModel fineTune = await OpenAI.instance.fineTune.create(
trainingFile: "FILE ID",
);
List fine-tunes
List<OpenAIFineTuneModel> fineTunes = await OpenAI.instance.fineTune.list();
Retrieve fine-tune
OpenAIFineTuneModel fineTune = await OpenAI.instance.fineTune.retrieve("FINE TUNE ID");
Cancel fine-tune
OpenAIFineTuneModel fineTune = await OpenAI.instance.fineTune.cancel("FINE TUNE ID");
List fine-tune events
List<OpenAIFineTuneEventModel> events = await OpenAI.instance.fineTune.listEvents("FINE TUNE ID");
Delete fine-tune
bool deleted = await OpenAI.instance.fineTune.delete("FINE TUNE ID");
Moderations #
Create moderation
OpenAIModerationModel moderationResult = await OpenAI.instance.moderation.create(
input: "I want to kill him",
);
Error Handling #
Any time an error happens from the OpenAI API ends (As Example: when you try to create an image variation from a non-image file ), a RequestFailedException
will be thrown automatically inside your Flutter / Dart app, you can use a try-catch
to catch that error, and make an action based on it:
try {
// This will throw an error.
final errorVariation = await OpenAI.instance.image.variation(
image: File(/*PATH OF NON-IMAGE FILE*/),
);
} on RequestFailedException catch(e) {
print(e.message);
print(e.statusCode)
}